Procedure
Data analysis
- Raw data was imported into Skyline to extract the features
corresponding to possible contaminants (ToDo: add references)
- For this purpose, the Molecular Contaminant List template was used
(Gomez-Zepeda et al., 2023; modified from Rardin, 2018)
- The feature area of extracted ion chromatograms was processed using
HowDirty to generate this report (Gomez-Zepeda et al.,
2023)
Warning
The algorithm used for peak picking in Skyline is simple and based
only on m/z and charge (z). Thus, some true contaminant peaks
(e.g. peptides) could be incorrectly assigned to contaminants
(i.e. false positives). Therefore, it is recommended to also look into
the Skyline file to evaluate other factors, such as patterns of
contaminant groups elution across the retention time.
Calculations within
HowDirty
- TICA = Total Ion Current Area
- Abundance (Normalized abundance) = TotalAreaMS1 / TICA
- TotalAbundance_ContaminantGroup = Sum (Abundance_ContaminantGroup)
across all the contaminants in one ContaminantGroup for one sample
- Abundance_total = Sum (Abundance) across all the contaminants for
one sample
- Contaminant-specific Risk level assessment was performed by
comparing the Abundance of the possible contaminants in each one of the
test samples (current data set) against thresholds previously
extrapolated from a reference data set (~ 1000s runs). These thresholds
are reported in
results/2021-231_FASP_filters_report_contaminants_20230719_1911.xlsx–>
ref_conta_tshd
- Sample level summary contaminant group assessment was performed by
comparing the TotalAbundance_ContaminantGroup against the summed
thresholds from each contaminant
- Sample level summary contaminant risk assessment was performed by
comparing the Abundance_total against the sample-level quantile
thresholds from the reference dataset
- These thresholds are reported in
results/2021-231_FASP_filters_report_contaminants_20230719_1911.xlsx–>
ref_conta_tshd_sample
Summary
risk evaluation (total contamination)
- Overall status: WARNING: You have
some dirty samples!
- Evaluation based on the total contaminant abundance
Global
- The piechart below shows the percentages of samples associated to
each risk level
- The results were exported to
results/2021-231_FASP_filters_report_contaminants_20230719_1911.xlsx
–> risk_summ_sampleset
- RiskLevel = “1) Very Low”, “2) Low”, “3) Medium”, “4) High”, “5)
Very High”, “6) No threshold in reference”

Conditions
boxplot
- Statistical difference was assessed by a Wilcoxon signed-rank
test

Sample (ordered by
name)
- The table can also be found in
results/2021-231_FASP_filters_report_contaminants_20230719_1911.xlsx
–> conta_summ_sample.
Sample (ordered by
abundance)
- The table can also be found in
results/2021-231_FASP_filters_report_contaminants_20230719_1911.xlsx
–> conta_summ_sample.
Contaminant group
- Contamination risk is calculated based on Abundance_total
- y axis is ordered from highest to lowest abundance
Contaminants per sample
- A summary of the Abundance per ContaminantGroup was calculated and
is reported in the annexed report
(results/2021-231_FASP_filters_report_contaminants_20230719_1911.xlsx
–> conta_summ_contaminantgroup).
- The Abundance of the contaminants are reported in the plots below
for all the samples in the data set.
- The Pseudochromatograms represent the Abundance in function of the
RentetionTime (Apex of the peak). Those can be useful to evaluate the
presence of the usual patterns of polymers, i.e. from small to larger
molecules; as well as the reproducibility of the RentetionTime across
replicates.
Pseudochromatograms (Abundance vs. RT)
Table
- The following table shows the results of possible contaminants
detected in each sample.
- An extended version of this table containing the Area and
Total-Ion-Count-Area (TICA) can also be found in
results/2021-231_FASP_filters_report_contaminants_20230719_1911.xlsx
–> conta.
- RiskLevel = “1) Very Low”, “2) Low”, “3) Medium”, “4) High”, “5)
Very High”, “6) No threshold in reference”
Appendix
- Result tables are exported in folder
results/2021-231_FASP_filters_report_contaminants_20230719_1911.xlsx.
References
- Gomez-Zepeda et al.. HowDirty. Under preparation.
(2023).
- Rardin, M. J. Rapid Assessment of Contaminants and Interferences in
Mass Spectrometry Data Using Skyline. J. Am. Soc. Mass Spectrom. 29,
1327–1330 (2018).